Hunting optical phenomena at the nanometer scale—performing nano-optics—is inherently paradoxical. On one hand, optical processes are governed by length scales comparable to the wavelength of visible light, typically a few hundred nanometers. On the other hand, the optical properties of nanostructures start to deviate from their bulk counterparts precisely when their size becomes smaller than this scale. Metallic nanoparticles, for instance, support plasmon resonances whose spectral features are extremely sensitive to subtle variations in size and shape. In other systems, such as quantum dots or quantum wells, atomic-scale structural details can become decisive.
To probe these effects, a whole class of experimental approaches has emerged over the past two decades to circumvent the optical diffraction limit, enabling access to the optical response of individual nanostructures and to the new physics they reveal.

In this talk, I will introduce a family of such techniques that use focused beams of free electrons—such as those available in a transmission electron microscope—to perform optical spectroscopy at the nanometer scale,  sometimes in conjunction with laser beams. I will show how these methods can map plasmons, excitons, photonic modes, and even phonons with unmatched spatial resolution. Beyond the beauty of the resulting images, I will discuss how these experiments can now be interpreted quantitatively in purely optical terms—extinction and scattering cross-sections, or electromagnetic local density of states. Finally, I will illustrate how recent developments in this field open the way to new classes of free-electron experiments, from quantum optical measurements to nanoscale thermometry.

Plasmonic nanoparticles have drawn tremendous interest in the scientific community due to their unique ability to interact with light via localized surface plasmons. Understanding the delicate interplay between particle morphology, composition and optical properties is of utmost importance in optimizing particle design for numerous applications. While single-particle spectrally-resolved measurements can reveal insights into the optical properties, electron microscopy (EM) can be utilized to study structural features. With the advances in complex nanoparticles' geometries, however, 2D EM techniques are no longer sufficient and the need for determining the 3D structure arises. In this talk, I will show examples of different strategies for correlating the optical properties of single plasmonic nanoparticles with their 3D morphology obtained from electron tomography. In particular, I will highlight how the combination with single-particle optical techniques opens up pathways for additional information inaccessible to electron-based techniques. Finally, I will discuss how quantified electron tomography is indispensable in unravelling structural changes in plasmonic nanoparticles driven by pulsed laser irradiation and our recent progress towards studying these modifications in situ inside the electron microscope.

Several candidate materials and structures show great promise for next generation photovoltaics and optoelectronic devices. The complete understanding of charge dynamics at the nanoscale, and in particular how local composition and crystallography affect transport phenomena, recombination and ultimately power conversion efficiency, is often a bottleneck in the development of architectures that can be deployed and have an impact outside of the research lab.

Transmission electron microscopy enables studies of elemental distributions as well as local morphology, with cross-sectional observation revealing variations through the depth of the absorber layer as well as quality of interfaces across all components of a device stack. Furthermore, recent developments in technique, hardware and software now enable the acquisition of electron diffraction patterns across micron-scale areas with a probe size of a few nm, yielding very local information on crystal phase and orientation. This approach, often referred to as 4DSTEM, generates very large, information-rich datasets. Their interpretation can be carried out manually, with careful analysis of selected regions, or through the use of unsupervised routines that extract information via the application of statistical methods.

In this study we looked at three candidate absorbers for next generation photovoltaics: evaporated halide perovskites, Cu(InGa)S₂ (CIGS) and Sb₂Se₃. While they all rely on optimisation of fabrication parameters in order to obtain the best optoelectronic parameters, each case presents different challenges. Halide perovskites are rapidly damaged by the electron beam, and need to be studied with a very low electron dose. CIGS combine a complex stoichiometry, requiring a fine tuning of the compositional gradient through the thickness, as well as featuring different types of grain boundaries, some of which are particularly detrimental to electron transport. Finally, Sb₂Se₃ films comprise a large number of small (tens of nm) crystallites, requiring fine sampling and computationally efficient routines to analyse the corresponding 4DSTEM datasets.

We employ a variety of unsupervised methods for extracting information from the datasets acquired on these systems: Non-negative Matrix Factorization, K-means clustering and Mini-batch K-means clustering. The strengths of each approach are highlighted and discussed.

The application of 4DSTEM to materials for optoelectronics is a very versatile tool that can address issues in a variety of promising candidate materials. With this work we demonstrate a framework for compositional and crystallographic studies at single-grain scale, with potential applications in new, emerging semiconductors.

Electron ptychography — a computational phase-contrast method that reconstructs the sample’s transmission function from overlapping scanning-diffraction patterns — is rapidly becoming a practical tool for resolving the atomic structure of complex nanomaterials far beyond conventional depth-of-focus and coherence limits. For materials synthesis and nanoscale structure–property research, this capability opens a new window into interfaces, confined phases, defect networks, and metastable structural motifs that govern functional behavior.
We present three recent advances that make 3D ptychographic imaging more broadly applicable to real nanomaterial systems. First, using tomographic 4D-STEM tilt-series acquisition, we resolve the atomic lattice of a Zr–Te phase confined in double-wall carbon nanotubes, demonstrating that ptychographic single-slice tomography can identify intricate polytypes and nanoscale structural distortions relevant to templated growth. Second, a multi-slice reconstruction coupled with joint tomographic alignment overcomes the depth-of-focus barrier of conventional linear tomography, enabling atomic-resolution imaging across tens of nanometers of heterogeneous material.
Third, we introduce an end-to-end reconstruction framework that incorporates all physical effects to achieve near-isotropic 0.8 Å 3D resolution even under extreme missing-wedge conditions. This makes it feasible to recover the internal structure of nanoparticles, nanowires, and confined phases from sparsely sampled or limited-angle datasets, as often required for beam-sensitive or geometrically constrained materials.
Finally, we will report on our efforts to extend ptychography into the in-situ regime by tracking the growth behavior of Ir/Ir-oxide nanoparticles inside ~60 nm-thick liquid cells. Imaging small nanocrystals in thick liquid with lattice resolution enables direct observation of nucleation pathways, redox dynamics, and morphological evolution under realistic electrochemical and synthesis conditions, connecting atomic-scale structure to functional performance.
Together, these developments turn 3D electron ptychography — in both ex-situ and in-situ modes — into a powerful platform for discovering how atomic arrangements shape the emergent properties of modern nanomaterials.

Much of our understanding of nanoscale materials comes from characterization techniques that reveal important aspects of structure, composition, morphology, and properties, among many other features. Structural characterization is particularly important, as crystal structure plays a foundational role in defining many other features of nanomaterials, including those listed above. Advanced structural characterization techniques provide increasingly sophisticated insights into how atoms are arranged within nanoscale materials. However, most researchers continue to emphasize routine structural characterization techniques that are readily available, such as powder X-ray diffraction. It is therefore important to fully harness the capabilities of such techniques, as well as to understand and appreciate the limitations. This talk will highlight how powder X-ray diffraction, a mainstream technique that is routinely applied to nanoscale materials systems, can be used alongside other materials characterization techniques to provide useful information, including phase evolution during synthesis, sample purity, and validation that the bulk of a sample matches key features observed microscopically. These topics will be discussed within a backdrop of compositionally complex colloidal nanoparticles, including heterostructured and high-entropy systems, where powder X-ray diffraction provides insights that are both complementary to, and distinct from, those obtainable by electron microscopy.

Characterizing the atomic structure of functional materials is essential for advancing technologies in energy storage, catalysis, and electronics. Powder X-ray diffraction (PXRD) remains a central tool for this task, providing average periodic structure even for nanomaterials where finite size and surface effects are present. Yet identifying a suitable crystallographic model directly from PXRD is difficult, as instrumental resolution limits and sample characteristics broaden or distort peaks, creating overlap and ambiguity. In parallel, generative and machine learning approaches to crystal structure prediction have progressed rapidly, but most operate on high-level descriptors such as composition or symmetry and do not incorporate diffraction data directly^1,2,3.This motivates a central question: how does PXRD conditioning shape the accuracy and uncertainty of generative crystal structure predictions?

To investigate this, we introduce deCIFer⁴, a PXRD-conditioned autoregressive transformer that generates full CIF structures from an encoded diffraction profile, with optional inputs such as composition or space group. deCIFer is trained on a large set of inorganic structures paired with simulated PXRD patterns and therefore provides a representative case study for PXRD-guided generative modelling.

We assess robustness through a unified evaluation combining synthetic perturbation experiments and real experimental PXRD. Synthetic tests apply physically motivated distortions to the input pattern, including unit-cell scaling, peak shifts, peak asymmetry, Scherrer broadening, additive noise and background variation. Across these conditions, we observe that PXRD conditioning improves structure prediction when diffraction features are sufficiently informative, producing tight sets of plausible structural candidates. As distortions increase, deCIFer transitions to broader structural distributions that reflect the diminishing information content of the PXRD, and when the signal becomes uninformative, the predictions revert toward statistically favored structures. Lastly, we evaluate the model on experimental PXRD from well-characterized bulk- and nanomaterial samples. In these cases, deCIFer provides reasonable structural candidates that capture the main diffraction features that can serve as starting models for downstream analysis. These results highlight that PXRD conditioning can improve the robustness of crystal structure prediction and support practical workflows in materials characterization.

Ordered assemblies of nanocrystals, called supercrystals, exhibit collective quantum phenomena, such as superfluorescence, arising from coupling between neighboring crystals [1]. In particular, lead-halide perovskite supercrystals have emerged as promising candidates for applications including light-emitting diodes, electro-optical modulators, and detectors for visible and X-ray radiation. However, the soft ligand shell surrounding individual nanocrystals makes the superlattice susceptible to structural defects, which diminish structural coherence and, consequently, affect their physical properties [2].

Advances in synchrotron sources and X-ray optics now make it possible to focus an X-ray beam to below 100 nm while maintaining sufficient intensity to record diffraction patterns. This enables spatially resolved characterization of these materials, providing insight into both the local superlattice structure and the atomic lattice of constituent nanocrystals [3]. Such capabilities allow direct correlation between supercrystal structure and their optical, electrical, and mechanical behavior. In this talk, we compare perovskite supercrystals synthesized via solvent-evaporation and two-layer phase-diffusion methods, highlighting how structural differences arising from these routes influence their material properties [4,5,6]. 

Understanding how materials evolve under non-equilibrium conditions requires experimental tools capable of capturing both local structural changes and their ultrafast dynamics. Ultrafast X-ray pair distribution function (uf-PDF) analysis—based on total scattering measurements enabled by femtosecond X-ray free-electron lasers (XFELs)—now allows direct access to transient local structures beyond the constraints of crystallographic symmetry and long-range orde Here, we will discuss how resolving hierarchical structural evolution on femtosecond to picosecond timescales provides critical insight into transient states and hidden orders that often govern the functional behavior of complex quantum materials [1].

Recent advances have demonstrated that high-quality total scattering data and corresponding PDFs can be obtained from a single ~30 fs XFEL pulse over an extended Q-range. This capability further enables detailed structural analysis of crystalline, nanocrystalline, amorphous, and liquid systems alike [2]. These developments open new frontiers for time-resolved investigations of lattice instabilities, correlated electron phenomena, and the competition between intertwined orders in quantum materials [3].

Despite sustained progress in the performance characteristics of organic semiconductors and halide perovskites, there are many fundamental features of structural and chemical heterogeneity that remain poorly understood. Resolving how specific features of structural and compositional heterogeneity limit properties is crucial for developing new interventions for the fabrication of devices with improved and more durable efficiency.  Advances in low-dose, nanometre resolved electron diffraction have enabled access to this information for linking nanoscale structure to characteristics underpinning charge transport mechanisms [1, 2] and device ageing [3]. When combined with spectroscopy in the scanning transmission electron microscope (STEM), diffraction tools can particularly offer a direct means to link optical properties to nanoscale structures [4]. This presentation will highlight ongoing work to probe the role of localised, crystallographic defects (including dislocations [5]), crystalline and amorphous interfaces in polymer semiconductors, as well as compositional heterogeneity in mixed anion lead halide perovskite nanocrystals within metal–organic framework glass composite materials. Respectively, these observations link disorder in perylene diimide (PDI) nanocrystals to a reduction in the exciton diffusion coefficient by over two orders of magnitude and elaborate models for the change in the Stokes shift and exciton radius with composition in halide perovskites. These examples underscore the need to further progress multiscale structural and spectroscopic probes adapted to emerging semiconductor materials to observe otherwise hidden mechanisms limiting performance.

Materials for Sustainable Development Conference (MATSUS 2026)

Hierarchical Zn-MOF Nanoarchitectures for Efficient Removal of Endocrine Disruptors from Aqueous Systems

Anam Afaq^a, Kartiki Chandratre^a, Mohammad Mohsin^a,b, Arghya Banerjee^a, and Sarang P. Gumfekar^a*

^aDepartment of Chemical Engineering, Indian Institute of Technology Ropar, Rupnagar, 140001, Punjab, India

^bCentre for Nanoscience and Nanotechnology, Jamia Millia Islamia, Delhi, 110025, India

*Corresponding author: sarang.gumfekar@iitrpr.ac.in

Metal–organic frameworks (MOFs) are promising nanoarchitectures for environmental remediation due to their tunable porosity and multifunctionality. In this work, two Zn-based MOF systems specifically designed to remove endocrine-disrupting chemicals (EDCs) from water are synthesized and characterized. A facile approach yielded CALF-20, exhibiting high adsorption capacities of 329.3 mg g⁻¹ for Bisphenol-A and 392.9 mg g⁻¹ for 17-α Ethinylestradiol. Multi-scale SAXS revealed a hierarchical structure comprising mesoscale aggregates and nanoscale lamellae. The adsorption kinetics and isotherm data conformed well to the pseudo-second-order and Langmuir models, respectively. Thermodynamic evaluation indicated that the adsorption process was both spontaneous and released heat, demonstrating its exothermic character. DFT and XPS identified hydrogen bonding, π–π interactions, and Zn–O bonds as primary adsorption mechanisms, with demonstrated selectivity and reusability. Furthermore, in batch and fixed-bed experiments, Zn/Ni MOFs embedded in κ-carrageenan/NH₄A beads shown enhanced 17β-estradiol removal efficacy, structural stability, and regeneration capability. The maximum adsorption capacity under continuous flow conditions was estimated at 450.11 mg g^-1 using the Thomas model. Molecular dynamics simulations indicated π–π stacking and hydrophilic interactions govern adsorption at the molecular level. These results demonstrate that Zn-based MOF nanoarchitectures are reliable, scalable options for sustainable environmental remediation as well as potential uses in chemical sensing and therapeutics.

The relationship between structure and properties is elementary for the applications of crystalline solids. Because of the increasing complexity in materials on different length scales, the development of advanced methods for structure analysis are needed.

In the shadow of X-ray crystallography, nearly 100 years after the discovery of the wave character of electrons, electron crystallography has evolved to encompass both imaging and diffraction techniques, enabling crystallographic analysis of micro- and nanostructures with atomic resolution.

Thanks to the development of the tomographic data acquisition 15 years ago, electron diffraction has been rediscovered and continuously developed since then, making it possible to analyse tiny single crystals analogous to single crystal X-ray diffraction. This allows nowadays, on the one hand, determining the structure of small particles, and on the other, to even investigate crystal structures of beam sensitive small molecule structures.^[1]

The extensive structural exploration of current material classes such as organic and layered materials,^[2,3] switchable semiconductors,^[4,5] porous catalysts,^[6] and battery materials^[7] is in numerous cases only successful with three-dimensional electron diffraction (3D ED). Therefore, the method has become highly attractive in the field of materials science.

Comprehending light-induced functionality in 2D superlattices of ligand-capped nanoparticles requires the direct observation of their interaction with light, in order to disentangle the complex interplay between electronic and structural degrees of freedom across a broad range of length scales, from building-blocks to their longer-range arrangement. Addressing these challenges critically needs new techniques capable of imaging with high spatial and temporal resolution, capable of achieving contrast to: core morphology (size, porosity, assembly), and ligand shells (distribution and composition).

Here, we present an Extreme Ultraviolet (EUV) Ultrafast Microscope relying on a technique for Coherent Diffractive Imaging called Ptychography, which is capable of full-field imaging with diffraction-limited spatial resolution, with  sensitivity to both material quantitative composition (amplitude) and morphological (phase) contrast.

We establish a robust protocol for 2D nanoparticle superlattices capable to visualize core morphology, orientational distribution, porosity. Moreover, we obtain contrast between the organic ligand shells and the core, showing that the ligand orientational distribution is directly linked to the surface morphology of the cores.

X-ray Absorption Fine Structure (XAFS), comprising XANES and EXAFS, has become a central tool for resolving local atomic and electronic structure in nanomaterials under relevant operando conditions. This talk will provide an introduction to this methodology, followed by selected state-of-the-art examples in batteries and heterogeneous catalysis.

First, the talk will focus on the practical fundamentals needed by non-specialists: what governs an absorption edge, how XANES fingerprints oxidation state, symmetry, and unoccupied density of states, and how EXAFS yields quantitative coordination numbers, bond lengths, and disorder parameters in the absence of long-range order. Emphasis will be placed on experimental design and on how analysis choices map to interpretable structural models.

The second half will show how these capabilities address two sustainability-critical areas: batteries and heterogeneous catalysis. For batteries, XAFS enables element-specific tracking of redox mechanisms, local phase evolution, and short-range reconstruction at interfaces during cycling. For catalysis, XAFS disentangles active-site speciation and coordination dynamics under reaction conditions, distinguishing spectator phases from true catalytic motifs and clarifying structure–activity relationships in supported nanoparticles.

Special emphasis will be put on the NOTOS beamline [1], with the capability to perform XAS and XRD investigations in a quasi-simultaneous way. NOTOS allows us to study the electronic structure and short- and long-range order within a wide range of scientific disciplines: chemistry, catalysis, energy-related science, nanomaterials, condensed matter and environmental science. In particular, NOTOS has been further developed to focus on in situ and operando measurements on heterogeneous catalysis, batteries [2] and electrochemistry in general.

Attendees will leave with concrete ideas for integrating XAFS into their own nanomaterials research to access local structure–property links that are inaccessible to diffraction-based approaches.

We report on the formation of metal nanoislands (Au, Ag, Al, Ti) and their plasmonic influence on subsequently deposited perovskite absorber layers. Initially, ultrathin metal films were deposited on quartz substrates and thermally annealed at temperatures between 500 °C and 700 °C to induce controlled dewetting and generate size-tunable nanoislands. These plasmonic nanostructures served as the underlying metallic template onto which the perovskite layer was later deposited. Post-annealing at 100 °C for 1 hour enabled further evolution of the metal nanoisland morphology, with higher temperatures (>500 °C) producing a Gaussian particle size distribution centered around ~25 nm. Optical characterization revealed a pronounced localized surface plasmon resonance (LSPR) near 500 nm with a broad spectral shoulder and tail, indicative of the wide nanoparticle size spread. When integrated beneath a perovskite absorber in a planar device configuration, these metal nanoislands significantly enhanced optical absorption and photocurrent generation, yielding improvements of up to 35.51%, strongly dependent on nanoisland size and surface density. This study highlights the strong potential of metal–perovskite plasmonic coupling for boosting light harvesting in next-generation solar cells.